| Interpreting neural decoding models using grouped model reliance S Valentin, M Harkotte, T Popov PLoS Computational Biology 16 (1), e1007148, 2020 | 10 | 2020 |
| Learning Hidden Causal Structure from Temporal Data S Valentin, NR Bramley, CG Lucas Proceedings of the Annual Meeting of the Cognitive Science Society 42 (42), 2020 | 5 | 2020 |
| Bayesian Optimal Experimental Design for Simulator Models of Cognition S Valentin, S Kleinegesse, NR Bramley, MU Gutmann, CG Lucas NeurIPS 2021 AI for Science Workshop, 2021 | 4 | 2021 |
| Symbolic and sub-symbolic systems in people and machines S Valentin, B Zhao, C Jiang, NR Bramley, C Lucas Proceedings of the Annual Meeting of the Cognitive Science Society 43 (43), 2021 | 4 | 2021 |
| Discovering common hidden causes in sequences of events S Valentin, NR Bramley, CG Lucas Computational Brain & Behavior 6 (3), 377-399, 2023 | 3 | 2023 |
| Designing optimal behavioral experiments using machine learning S Valentin, S Kleinegesse, NR Bramley, P Seriès, MU Gutmann, ... Elife 13, e86224, 2024 | 2 | 2024 |
| Bayesian experimental design for intractable models of cognition S Valentin, S Kleinegesse, NR Bramley, M Gutmann, C Lucas Proceedings of the annual meeting of the Cognitive Science Society 43 (43), 2021 | 2 | 2021 |
| Naïve information aggregation in human social learning JP Fränken, S Valentin, CG Lucas, NR Bramley Cognition 242, 105633, 2024 | 1 | 2024 |
| Know your network: Sensitivity to structure in social learning JP Fränken, S Valentin, C Lucas, NR Bramley Proceedings of the Annual Meeting of the Cognitive Science Society 43 (43), 2021 | 1 | 2021 |
| Probabilistic demand forecasting with graph neural networks N Kozodoi, E Zinovyeva, S Valentin, J Pereira, R Agundez arXiv preprint arXiv:2401.13096, 2024 | | 2024 |
Christopher G. LucasUniversity of EdinburghVerified email at ed.ac.uk
